Development of a Framework for Implementation of Maintenance Tools and Techniques Using Interpretive Structural Modeling

Patidar, Lakhan; Soni, Vimlesh Kumar; Soni, Pradeep Kumar

doi:10.1016/j.matpr.2017.07.157

Cited by 7 publications

(12 citation statements)

References 19 publications

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“…Very few studies mention usage of some software for transitivity calculations such as [56,57]. However, one of the most frequent reasons for incorrect ISM calculations have been wrong transitivity calculations, such as in studies [9,13,16,[23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. Therefore, this study proposes the use of an established Warshall algorithm [67] for transitivity calculations.…”

Section: Structural Self-interaction Matrix (Ssim)mentioning

confidence: 99%

“…Further they are connected with directional edges based upon 1s or 1*s in the CM between pairs of variables. Fewer studies have mentioned CM and digraph [12,20,27,35,65,[68][69][70], as the digraph resembles the final model with a lesser number of edges. The importance of the digraph further goes down in automatic calculation of transitivity.…”

Section: Conical Matrix (Cm) and Digraphmentioning

confidence: 99%

“…There are two approaches followed for decision making, namely, discourse and survey. For discourse many techniques have adopted such as idea engineering workshops [40,60], telephonic enquiries [43,44], group decision making [13,52], personal interview [70,78], brainstorming [16,33,34,66], laddering interview [39], direct meetings [44], semi-structured interview [21,58,93] and structured interview [69], Delphi technique [37,61], and focus group discussion [11,27]. Similarly, for surveys different techniques are as follows: individual and consensus questionnaire [43], Likert scale questionnaire [78,90], email questionnaire [44], library survey method [9], and self-administered questionnaire [46].…”

Section: Decision Making and Data Collection Techniquesmentioning

confidence: 99%

“…Two studies [59,89] didn't provide RM, and their FRM didn't match with the SmartISM output due to wrong transitivity calculations. Furthermore, eighteen studies [9,13,16,[23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] had incorrect transitivity calculations leading to variations in FRM. Five studies [38][39][40][41][42] had variations at the fourth step of level partitioning.…”

Section: Assessment Of Application Of Ism Technique Using Smartismmentioning

confidence: 99%

“…Implementation of this technique and conduction of brainstorming sessions with experts in previous studies [17,18] led to identification of some key challenges such as variables' identification, selection of decision makers and method of decision making, and unavailability of end-to-end software for ISM and MICMAC. Furthermore, the literature shows erroneous applications of steps of ISM such as wrong reachability matrix [19][20][21][22], wrong transitivity calculations [9,13,16,[23][24][25][26][27][28][29][30][31][32][33][34][35][36][37], incorrect level partitioning and wrong structure of the model [31,[38][39][40][41][42], and incorrect addition [11,14,[43][44][45][46][47][48] or reduction [49][50][51][52] of edges affecting the reachability of variables. An error in an earlier step generally leads to an error in subsequent steps.…”

Section: Introductionmentioning

confidence: 99%

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SmartISM: Implementation and Assessment of Interpretive Structural Modeling

Ahmad

Qahmash

2021

Sustainability

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Interpretive Structural Modeling (ISM) is a technique to establish the interrelationships between elements of interest in a specific domain through experts’ knowledge of the context of the elements. This technique has been applied in numerous domains and the list continues to grow due to its simplistic concept, while sustainability has taken the lead. The partially automated or manual application of this technique has been prone to errors as witnessed in the literature due to a series of mathematical steps of higher-order computing complexity. Therefore, this work proposes to develop an end-to-end graphical software, SmartISM, to implement ISM technique and MICMAC (Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (cross-impact matrix multiplication applied to classification)), generally applied along with ISM to classify variables. Further, a scoping review has been conducted to study the applications of ISM in the previous studies using Denyer and Tranfield’s (2009) framework and newly developed SmartISM. For the development of SmartISM, Microsoft Excel software has been used, and relevant algorithms and VBA (Visual Basic for Applications) functions have been illustrated. For the transitivity calculation the Warshall algorithm has been used and a new algorithm reduced conical matrix has been introduced to remove edges while retaining the reachability of variables and structure of digraph in the final model. The scoping review results demonstrate 21 different domains such as sustainability, supply chain and logistics, information technology, energy, human resource, marketing, and operations among others; numerous types of constructs such as enablers, barriers, critical success factors, strategies, practices, among others, and their numbers varied from 5 to 32; number of decision makers ranged between 2 to 120 with a median value of 11, and belong to academia, industry, and/or government; and usage of multiple techniques of discourse and survey for decision making and data collection. Furthermore, the SmartISM reproduced results show that only 29 out of 77 studies selected have a correct application of ISM after discounting the generalized transitivity incorporation. The outcome of this work will help in more informed applications of this technique in newer domains and utilization of SmartISM to efficiently model the interrelationships among variables.

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